Emotions in online rumor diffusion

Abstract Emotions are regarded as a dominant driver of human behavior, and yet their role in online rumor diffusion is largely unexplored. In this study, we empirically study the extent to which emotions explain rumors. We analyze large-scale sample 107,014 rumors from Twitter, well cascades. For each rumor, embedded were measured based on eight so-called basic Plutchik’s wheel (i.e., anticipation–surprise, anger–fear, trust–disgust, joy–sadness). then estimated using generalized linear regression model how associated with spread terms (1) cascade size, (2) lifetime, (3) structural virality. Our results suggest that conveying anticipation, anger, trust generate more reshares, over longer time horizons, become viral. contrast, smaller virality found for surprise, fear, disgust. further presence 24 dyadic emotional interactions feelings composed two emotions) dynamics. Here, find cascades high degrees aggressiveness larger longer-lived, Altogether, important determinants spreading